253 lines
7.0 KiB
Go
253 lines
7.0 KiB
Go
/*
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* Copyright 2020 The Dragonfly Authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package searcher
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import (
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"context"
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"errors"
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"fmt"
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"sort"
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"strings"
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"github.com/mitchellh/mapstructure"
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logger "d7y.io/dragonfly/v2/internal/dflog"
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"d7y.io/dragonfly/v2/manager/model"
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"d7y.io/dragonfly/v2/pkg/rpc/manager"
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"d7y.io/dragonfly/v2/pkg/util/mathutils"
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)
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const (
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// Condition security domain key
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ConditionSecurityDomain = "security_domain"
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// Condition IDC key
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ConditionIDC = "idc"
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// Condition netTopology key
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ConditionNetTopology = "net_topology"
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// Condition location key
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ConditionLocation = "location"
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)
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const (
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// SecurityDomain affinity weight
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securityDomainAffinityWeight float64 = 0.4
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// IDC affinity weight
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idcAffinityWeight float64 = 0.3
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// NetTopology affinity weight
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netTopologyAffinityWeight = 0.2
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// Location affinity weight
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locationAffinityWeight = 0.1
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)
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const (
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// Maximum score
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maxScore float64 = 1.0
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// Minimum score
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minScore = 0
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)
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const (
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// Maximum number of elements
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maxElementLen = 5
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)
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// Scheduler cluster scopes
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type Scopes struct {
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IDC string `mapstructure:"idc"`
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Location string `mapstructure:"location"`
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NetTopology string `mapstructure:"net_topology"`
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}
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type Searcher interface {
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// FindSchedulerClusters finds scheduler clusters that best matches the evaluation
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FindSchedulerClusters(context.Context, []model.SchedulerCluster, *manager.ListSchedulersRequest) ([]model.SchedulerCluster, error)
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}
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type searcher struct{}
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func New(pluginDir string) Searcher {
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s, err := LoadPlugin(pluginDir)
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if err != nil {
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logger.Info("use default searcher")
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return &searcher{}
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}
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logger.Info("use searcher plugin")
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return s
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}
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// FindSchedulerClusters finds scheduler clusters that best matches the evaluation
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func (s *searcher) FindSchedulerClusters(ctx context.Context, schedulerClusters []model.SchedulerCluster, client *manager.ListSchedulersRequest) ([]model.SchedulerCluster, error) {
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conditions := client.HostInfo
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if len(conditions) <= 0 {
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return nil, errors.New("empty conditions")
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}
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if len(schedulerClusters) <= 0 {
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return nil, errors.New("empty scheduler clusters")
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}
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clusters := FilterSchedulerClusters(conditions, schedulerClusters)
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if len(clusters) == 0 {
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return nil, fmt.Errorf("security domain %s does not match any scheduler cluster", conditions[ConditionSecurityDomain])
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}
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sort.Slice(
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clusters,
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func(i, j int) bool {
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var si, sj Scopes
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if err := mapstructure.Decode(clusters[i].Scopes, &si); err != nil {
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logger.Errorf("cluster %s decode scopes failed: %v", clusters[i].Name, err)
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return false
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}
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if err := mapstructure.Decode(clusters[j].Scopes, &sj); err != nil {
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logger.Errorf("cluster %s decode scopes failed: %v", clusters[i].Name, err)
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return false
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}
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return Evaluate(conditions, si, clusters[i].SecurityGroup.SecurityRules) > Evaluate(conditions, sj, clusters[j].SecurityGroup.SecurityRules)
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},
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)
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return clusters, nil
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}
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// Filter the scheduler clusters that dfdaemon can be used
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func FilterSchedulerClusters(conditions map[string]string, schedulerClusters []model.SchedulerCluster) []model.SchedulerCluster {
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var clusters []model.SchedulerCluster
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securityDomain := conditions[ConditionSecurityDomain]
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for _, schedulerCluster := range schedulerClusters {
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// There are no active schedulers in the scheduler cluster
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if len(schedulerCluster.Schedulers) == 0 {
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continue
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}
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// Dfdaemon security_domain does not exist, matching all scheduler clusters
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if securityDomain == "" {
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clusters = append(clusters, schedulerCluster)
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continue
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}
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// Scheduler cluster is default, matching all dfdaemons
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if schedulerCluster.IsDefault {
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clusters = append(clusters, schedulerCluster)
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continue
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}
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// Scheduler cluster SecurityRules does not exist, matching all dfdaemons
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if len(schedulerCluster.SecurityGroup.SecurityRules) == 0 {
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clusters = append(clusters, schedulerCluster)
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continue
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}
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// If security_domain exists for dfdaemon and
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// scheduler cluster SecurityRules also exists,
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// then security_domain and SecurityRules are equal to match.
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for _, securityRule := range schedulerCluster.SecurityGroup.SecurityRules {
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if strings.EqualFold(securityRule.Domain, securityDomain) {
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clusters = append(clusters, schedulerCluster)
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}
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}
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}
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return clusters
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}
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// Evaluate the degree of matching between scheduler cluster and dfdaemon
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func Evaluate(conditions map[string]string, scopes Scopes, securityRules []model.SecurityRule) float64 {
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return securityDomainAffinityWeight*calculateSecurityDomainAffinityScore(conditions[ConditionSecurityDomain], securityRules) +
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idcAffinityWeight*calculateIDCAffinityScore(conditions[ConditionIDC], scopes.IDC) +
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locationAffinityWeight*calculateMultiElementAffinityScore(conditions[ConditionLocation], scopes.Location) +
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netTopologyAffinityWeight*calculateMultiElementAffinityScore(conditions[ConditionNetTopology], scopes.NetTopology)
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}
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// calculateSecurityDomainAffinityScore 0.0~1.0 larger and better
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func calculateSecurityDomainAffinityScore(securityDomain string, securityRules []model.SecurityRule) float64 {
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if securityDomain == "" {
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return minScore
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}
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if len(securityRules) == 0 {
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return minScore
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}
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return maxScore
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}
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// calculateIDCAffinityScore 0.0~1.0 larger and better
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func calculateIDCAffinityScore(dst, src string) float64 {
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if dst == "" || src == "" {
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return minScore
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}
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if strings.EqualFold(dst, src) {
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return maxScore
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}
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// Dst has only one element, src has multiple elements separated by "|".
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// When dst element matches one of the multiple elements of src,
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// it gets the max score of idc.
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srcElements := strings.Split(src, "|")
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for _, srcElement := range srcElements {
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if strings.EqualFold(dst, srcElement) {
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return maxScore
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}
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}
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return minScore
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}
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// calculateMultiElementAffinityScore 0.0~1.0 larger and better
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func calculateMultiElementAffinityScore(dst, src string) float64 {
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if dst == "" || src == "" {
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return minScore
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}
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if strings.EqualFold(dst, src) {
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return maxScore
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}
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// Calculate the number of multi-element matches divided by "|"
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var score, elementLen int
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dstElements := strings.Split(dst, "|")
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srcElements := strings.Split(src, "|")
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elementLen = mathutils.MaxInt(len(dstElements), len(srcElements))
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// Maximum element length is 5
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if elementLen > maxElementLen {
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elementLen = maxElementLen
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}
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for i := 0; i < elementLen; i++ {
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if !strings.EqualFold(dstElements[i], srcElements[i]) {
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break
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}
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score++
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}
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return float64(score) / float64(maxElementLen)
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}
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